MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic ProgrammingDownload PDF

16 Oct 2019 (modified: 22 Oct 2023)AABI 2019Readers: Everyone
Keywords: Probabilistic Programming, Causal Reasoning, Counterfactual Inference, Causality, Counterfactual, Importance Sampling
TL;DR: Probabilistic Programming that Natively Supports Causal, Counterfactual Inference
Abstract: We elaborate on using importance sampling for causal reasoning, in particular for counterfactual inference. We show how this can be implemented natively in probabilistic programming. By considering the structure of the counterfactual query, one can significantly optimise the inference process. We also consider design choices to enable further optimisations. We introduce MultiVerse, a probabilistic programming prototype engine for approximate causal reasoning. We provide experimental results and compare with Pyro, an existing probabilistic programming framework with some of causal reasoning tools.
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